3 citations · 7 across the 11 of their papers we have counts for
11 papers
Resource-adaptive distributed fault tolerance with very noisy Bell pairs
Moritz Schmidt, Martin Moureau, Benjamin Rodatz +3
Distributed architectures have been proposed as a pathway to large-scale quantum computers. Combined with the need for fault-tolerance, such architectures require distributed quant…
Iterative linear quadratic regulator on SU(N) for multi-qubit gate synthesis
Dirk Heimann, Felix Wiebe, Elie Mounzer +1
In quantum optimal control theory, gradient-based trajectory optimization techniques have proven versatile in designing multi-qubit quantum gates. Furthermore, incorporating the un…
Tensor Network Lattice Boltzmann Method for Data-Compressed Fluid Simulations
Lukas Gross, Elie Mounzer, David M. Wawrzyniak +2
Resolving unsteady transport phenomena in geometrically complex domains is traditionally constrained by polynomial scaling of computational cost with spatial resolution. While meth…
A partition function framework for estimating logical error curves in stabilizer codes
Leon Wichette, Hans Hohenfeld, Elie Mounzer +1
Based on the mapping between stabilizer quantum error correcting codes and disordered statistical mechanics models, we define a ratio of partition functions that measures the succe…
Explaining Anomalies with Tensor Networks
Hans Hohenfeld, Marius Beuerle, Elie Mounzer
Tensor networks, a class of variational quantum many-body wave functions have attracted considerable research interest across many disciplines, including classical machine learning…
Iterative Linear Quadratic Regulator for Quantum Optimal Control
Dirk Heimann, Felix Wiebe, Tahereh Abad +4
Quantum optimal control for gate optimization aims to provide accurate, robust, and fast pulse sequences to achieve gate fidelities on quantum systems below the error correction th…
Exploration of Design Alternatives for Reducing Idle Time in Shor's Algorithm: A Study on Monolithic and Distributed Quantum Systems
Moritz Schmidt, Abhoy Kole, Leon Wichette +3
Shor's algorithm is one of the most prominent quantum algorithms, yet finding efficient implementations remains an active research challenge. While many approaches focus on low-lev…
Quantum-inspired Embeddings Projection and Similarity Metrics for Representation Learning
Ivan Kankeu, Stefan Gerd Fritsch, Gunnar Schönhoff +3
Over the last decade, representation learning, which embeds complex information extracted from large amounts of data into dense vector spaces, has emerged as a key technique in mac…
Learning Fourier series with parametrized quantum circuits
Dirk Heimann, Hans Hohenfeld, Gunnar Schönhoff +2
Variational quantum algorithms (VQAs) and their applications in the field of quantum machine learning through parametrized quantum circuits (PQCs) are thought to be one major way o…
Weight-finite modules over the quantum affine and double quantum affine algebras of type
Elie Mounzer, Robin Zegers
We define the categories of weight-finite modules over the type quantum affine algebra and over the type double…
On double quantum affinization: 1. Type
Elie Mounzer, Robin Zegers
We define the double quantum affinization of type as a topological Hopf algebra. We prove that it admits a subalgebra $\ddot{\…